With the advent of commercial digital cameras, amateur photographers are able to experiment with the digital camera in situations with low light, such as evening or night sky pictures. Some of the best features of the commercial digital camera are that feedback is immediate and that photographers are unconstrained by a finite amount of film.
In low-light conditions, such as dawn, dusk, and night, amateur photographers can capture the dramatic effects of the unique play of light. This requires significantly long exposures which create some issues for digital cameras.
In contrast to traditional film cameras, which use film to capture pictures, digital cameras use electronic sensors such as a charge-coupled device (or CCD) or complementary metal-oxide semiconductor (or CMOS) devices to record all relevant information for each picture. Unlike film, which records visible light exactly as it strikes the film, the image sensor of the digital camera records raw data values where the range [0 . . . 4095] corresponds to quantized values of the light levels that strike the image sensor. This is the difference between analog in the traditional film camera, and the digital camera. In this situation, longer exposures are used to take high-resolution pictures in low-light, such as at dusk or night, or simply dark images.
When using long exposures, typically between 0.33 to 4 seconds or greater, depending on the sensor and ambient temperature, the image sensor reveals its inaccuracy. The image sensor records the data of the image through electrons collected via photoelectric conversion in each pixel. Unfortunately, some electrons build up in the pixel sites via other methods such as through metal impurities in the crystal structure and defects in the crystal lattice. In long-exposure night-sky pictures, these generated electrons produce images that resemble stars, and can substantially distort the image. Because this phenomenon is most noticeable under no-light conditions, these generated electrons are called “dark current.”
The warmth of the image sensor chip directly influences the of electrons generated; the amount of dark current in each pixel approximately doubles for every 8° C. increase. The amount of dark current is directly related to each pixel site, mostly by levels of defects. Hence, there is a fixed pattern across a sensor at a given temperature and integration time.
When two pictures of pure darkness, such as two pictures with the shutter closed or two pictures taken with the lens cap on, are compared with each other, the pictures will be nearly identical, pixel-by-pixel, aside from low-level variations from other noise sources. Most importantly, the two pictures will have the same amount of dark current at exactly the same pixel sites. When it is known that dark current in a digital camera, dependent on the ambient temperature, is fixed or static and always occurs in the same pixel locations, then the effects of dark current can be easily minimized.
However, the effects of dark current are more complicated than this and cannot be corrected so easily. In a single pixel measured over time, the amount of dark current generated over several frames would follow a Poisson distribution. This variation or uncertainty is called “dark current shot noise.” While the fixed pattern noise is easy to subtract, the shot noise is random and may leave noise in the image after subtraction. As the image sensor warms, more electrons are generated and the image recorded by the image sensor becomes noisier and more inaccurate.
Scientific digital cameras and professional astrophotographers use several different techniques to reduce dark current and dark shot noise. One technique to reduce the effects of dark current is to use cryogenic cooling systems. At very cold temperatures, the effects of dark current are almost entirely eliminated. However, rather than employing expensive cryogenic cooling systems on the consumer-grade digital camera, an easier and less expensive solution is currently employed.
Currently, the professional photographer using a digital camera to experiment with low-light photography will take a long-exposure picture and will, at approximately the same time, in order to record dark current of the camera at that ambient temperature, take another picture of darkness, i.e., with the shutter closed or the lens cap on the camera. This second image is called a “dark frame” or a “dark field.” The first image consists of a scene plus noise, including dark current, and the second image consists of dark current shot noise. Using a standard image editor, the two images can be subtracted, and the resultant image is the scene with no dark current noise. A disadvantage of this technique is that images received from a digital camera are usually not raw data but instead are usually subject to lossy processing, storage, and compression algorithms. Thus, when two lossy images are processed by the photographer, such as when a dark frame is subtracted from a picture image, then the accuracy of the resulting image is reduced from that of an image produced from the raw data.
Another disadvantage of this technique is that it does not reduce dark shot noise. When, at any given pixel, because of dark shot noise, the output level of the dark frame has a higher value than the output from the actual image, the resulting value from the subtraction is negative. Currently, when the photo editing software used by the professional photographer encounters negative values of data for a scene, the software automatically returns the negative values to zero. This will create inaccurate black spots or speckles called “clipping artifacts” in a picture.
In a picture of a night sky at dusk, for example, a dark blue background has white points of light that can be identified as stars. However, some of these white points of light are actually instances of dark current shot noise. When a dark frame is subtracted from the picture, the white points at the pixels with dark current shot noise are removed. If the random noise of the picture and the dark frame is low, then the dark frame subtraction will yield an accurate picture. However, when the random noise of the picture and the dark frame are combined to induce clipping artifacts, then the picture of the night sky will contain black points in place of the white points of light. While these black points will not be mistaken for stars, they are inaccuracies that detract from the final image.
A dark shot reduction technique of professional astrophotographers is to take multiple dark frame images, usually more than five, average the images pixel-by-pixel, and then subtract the averaged dark frame from the picture to create an image with reduced dark shot noise. While effective, this requires multiple dark frames, which must be taken by the photographer. In addition, that average dark frame is only valid for a given exposure time and temperature, and limits the number of picture images that can be taken by filling the memory of the digital camera. For amateur photographers, a simpler technique that does not limit the number of possible pictures to be taken is required.
There is a need, then, for a camera that will employ dark frame subtraction of only one dark frame before further processing, recognize when the data for an image is negative, and, rather than set that value to zero and thereby introduce spatial noise as a result of dark shot noise, will use value replacement to correct the pixel in place of creating black spots in an image. Typically, pixel replacement algorithms involve using information from neighboring pixels.